RNA-seq analysis of human iPSC derived Hepatocyte organoids (iHOs), 2D-iPS-Heps, iPS-HPCs, iPSCs, and other iPSC derived organoids cultured in woBA medium and fetal organoid medium
Single-cell RNA-seq · human · 30 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 30 samples: 15 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE248110_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1041784 and SRA study SRP472549. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 30 samples.
How we read this: 15 replicated groups read from 30 sample titles; they account for 30 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM7906026 FO1_P1_1 FO1_P1
- GSM7906027 FO1_P1_2 FO1_P1
- GSM7906028 iHOwoBA1_P1_1 iHOwoBA1_P1
- GSM7906029 iHOwoBA1_P1_2 iHOwoBA1_P1
- GSM7906030 iHOTCA1_P1_1 iHOTCA1_P1
- GSM7906031 iHOTCA1_P1_2 iHOTCA1_P1
- GSM7906032 iHO1_P1_1 iHO1_P1
- GSM7906033 iHO1_P1_2 iHO1_P1
- GSM7906034 FO1_P3_1 FO1_P3
- GSM7906035 FO1_P3_2 FO1_P3
- GSM7906036 iHOwoBA1_P3_1 iHOwoBA1_P3
- GSM7906037 iHOwoBA1_P3_2 iHOwoBA1_P3
- GSM7906038 iHOTCA1_P3_1 iHOTCA1_P3
- GSM7906039 iHOTCA1_P3_2 iHOTCA1_P3
- GSM7906040 iHO1_P3_1 iHO1_P3
- GSM7906041 iHO1_P3_2 iHO1_P3
- GSM7906042 FO2_P3_1 FO2_P3
- GSM7906043 FO2_P3_2 FO2_P3
- GSM7906044 iHOwoBA2_P3_1 iHOwoBA2_P3
- GSM7906045 iHOwoBA2_P3_2 iHOwoBA2_P3
- GSM7906046 iHO2_P3_1 iHO2_P3
- GSM7906047 iHO2_P3_2 iHO2_P3
- GSM7906048 iHO3_P3_1 iHO3_P3
- GSM7906049 iHO3_P3_2 iHO3_P3
- GSM7906050 iPSHep_1 iPSHep
- GSM7906051 iPSHep_2 iPSHep
- GSM7906052 iPSHPC_1 iPSHPC
- GSM7906053 iPSHPC_2 iPSHPC
- GSM7906054 iPSC_1 iPSC
- GSM7906055 iPSC_2 iPSC
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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.